Obstructive sleep apnea (OSA) significantly increases the risk of cardiovascular events in patients with acute coronary syndrome (ACS), yet the underlying metabolic mechanisms remain unclear. This study aims to analyze the metabolic characteristics of ACS patients with OSA using metabolomics based on a prospective cohort. The study intends to construct an artificial intelligence-based risk stratification model to improve prognosis prediction and facilitate precision medicine for this population.
Age 18-85 years.
Diagnosed with ACS, including ST-segment elevation myocardial infarction, non-ST-segment elevation myocardial infarction, and unstable angina.
Willing to participate and sign the informed consent form.
Cardiogenic shock or cardiac arrest.
Central sleep apnea or other types of sleep disordered breathing.
Previous or current treatment with continuous positive airway pressure.
Inability to complete polysomnography or invalid data.